Whether working in the private or public sector, projects are a critical part of any organization. Projects could be R&D, engineering, marketing campaigns, human resources, new factory or even IT projects. These projects represent a wealth of data that should make any data management professional salivate, but more often than not, project analytics are overlooked.
For decades, R&D, engineering and other areas have embraced a very structured project management approach. This project management approach is more than just putting a plan in Microsoft Projects. It is a structured, metric-based approach.
Just like any other business area with data, there is an opportunity for the business-aware data management professional to add value through analytics and business intelligence.
Projects produce a richness of metrics that need to be understood and analyzed by the data management professional. Three ways to analyze the metrics are: top down, bottom up and middle out.
The top-down approach looks at the overall objectives of the project and breaks them down into metrics that can be measured. In this case, understanding how executive management will measure the success of the project is critical. Will it be measured by on-time completion date, finishing within budget, usage of eco-friendly products, building of reusable plant components or other measures that are critical at the executive management level?
Once the top-level objectives are understood, supporting metrics can be drawn from the project. The project plan, actuals, budget and financial statements are the first places to look. In support of the objectives, metrics from these systems can be gathered. For example, if the key measurement is on-time delivery, measurement of the planned interim milestones versus actual dates is an obvious place to go.
Each objective should have at least one metric to measure project success/failure rates.
Top down: Start with goals and objectives and drill down to metrics.
The bottom-up approach looks at the project from the project manager's level first. He or she will need key metrics to provide insight into the health of the project. Although many metrics will be the same as the top down, there will also be a host of new metrics which are key to the project manager. Examples of these metrics include staffing levels (are the staff expectations under- or overallocated?) and material consumption metrics (are the waste expectations being met?). By concentrating on the bottom up, the strength is that the details will provide the baseline for a rollup to the executive-appropriate metrics.
Bottom up has become less feasible as the applicability of metrics to various types of projects has greatly increased. The raw time needed to interview and collect information in a bottom-up fashion often makes the effort cost-ineffective. This has led to a new way of gathering project analytics, middle out.
Bottom up: Start with the line-level project managers' needs and build upward.
In the middle-out method, a midpoint between the executive metrics and the day-to-day project metrics is selected as the starting point. The details needed for the line managers are then outlined in a drill-down approach, and the higher-level executive metrics are aggregated up from the starting point. In project metrics, a common entry point for middle out is the project milestone. Using an example of a marketing campaign project, key milestones may be: budget establishment, target market selection, vendor contracting and initial messaging, among others. The key is to pick milestones that can be driven down to lower levels by the project manager analytic user and can roll up for the executives.
For example, the variance of meeting vendors contracting milestones can be further drilled down to the subtasks leading up to the milestone. In contrast, the executive metrics can be a rollup along the lines of number of key milestones met or average variance dollars at key milestones.
This ability to both drill up and down (and across) gives the flexibility of analysis that is possible with a pure bottom-up approach but with less time and labor.
Middle out: Pick an analysis level between top down and bottom up, then aggregate it and drill down to determine line manager and executive needs.
In building project-analytic applications, there have historically been three approaches. The top-down approach, although aligned with executive needs, does not offer the rich metrics needed to take action at the project level. The bottom-up approach often is too detail oriented and labor intensive in the gathering of requirements. Middle out, by selecting the right midpoint analytic level, such as key milestones, allows drill down to the line-manager details, along with aggregation for executive visibility.
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